Papers with English-Arabic
Generating Image Captions in Arabic using Root-Word Based Recurrent Neural Networks and Deep Neural Networks (N18-4)
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| Challenge: | Existing studies on image caption generation in English focus on Western languages, ignoring Semitic and Middle-Eastern languages like Arabic, Hebrew, Urdu and Persian. |
| Approach: | They propose to leverage the critical dependency of Arabic to generate Arabic captions using root-word based Recurrent Neural Network and Deep Neural networks. |
| Outcome: | The proposed model outperforms English-Arabic translated captions on a dataset from newspapers in the Middle East. |
A Discriminative Neural Model for Cross-Lingual Word Alignment (D19-1)
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| Challenge: | a novel word alignment model for machine translation has been developed for a number of languages . explicit word-to-word alignments have largely been lost in neural MT systems . |
| Approach: | They propose a discriminative word alignment model which integrates into a Transformer-based machine translation model. |
| Outcome: | The proposed model performs better on Chinese and Arabic alignments than standard models. |